Fast Motion Estimation Using N-Queen Pixel Decimation
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A 2-Stage Partial Distortion Search Algorithm for Block Motion Estimation
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A High Quality/Low Computational Cost Technique for Block Matching Motion Estimation
Proceedings of the conference on Design, Automation and Test in Europe - Volume 3
Motion identification from image sequences: Information theory and pixel selection
Computers & Mathematics with Applications
Fast and accurate global motion estimation algorithm using pixel subsampling
Information Sciences: an International Journal
New pixel-decimation patterns for block matching in motion estimation
Image Communication
Error-resilient motion estimation architecture
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
New motion compensation model VIA frequency classification for fast video super-resolution
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A content-motion-aware motion estimation for quality-stationary video coding
EURASIP Journal on Advances in Signal Processing
A neighborhood elimination approach for block matching in motion estimation
Image Communication
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A new adaptive technique based on pixel decimation for the estimation of motion vector is presented. In a traditional approach, a uniform pixel decimation is used. Since part of the pixels in each block do not enter into the matching criterion, this approach limits the accuracy of the motion vector. In this paper, we select the most representative pixels based on image content in each block for the matching criterion. This is due to the fact that high activity in the luminance signal such as edges and texture mainly contributes to the matching criterion. Our approach can compensate the drawback in standard pixel decimation techniques. Computer simulations show that this technique is close to the performance of the exhaustive search with significant computational reduction